IMDb Sentiment Analysis Classifier

# IMDb Sentiment Analysis Classifier

Developed a **Sentiment Analysis** model to classify **IMDb movie reviews** as **Positive** or **Negative** using Natural Language Processing (NLP) and Machine Learning techniques.

The project involved cleaning and preprocessing text data, converting reviews into numerical features, training and evaluating classification models, and predicting the sentiment of new movie reviews. The goal was to accurately identify users' opinions based on the review text.

**Technologies Used:**

* Python

* Natural Language Processing (NLP)

* Scikit-learn

* Pandas

* NumPy

* TF-IDF Vectorization

**Key Features:**

* Text preprocessing (tokenization, stopword removal, and cleaning).

* Feature extraction using TF-IDF.

* Binary sentiment classification (Positive/Negative).

* Model training and performance evaluation.

* Predicts sentiment for unseen IMDb reviews.